Current cancer drug targets最新文献

Introduction: There is no consensus on the impact of young age (≤ 35 or 40) on breast cancer prognosis. In this study, a meta-analysis was carried out on the prognosis of breast cancer in young women.

Methods: We searched PubMed, Embase, Web of Science, Cochrane, and key cancer-related international conference proceedings, from their inception to 1st June, 2023, with an update on 15th July, 2023. Studies were included if they reported hazard ratios (HRs) with 95% confi-dence intervals (CIs) or presented Kaplan-Meier survival curves. The main outcomes were overall survival (OS), disease-free survival (DFS), breast cancer-specific survival (BCSS), lo-cal recurrence-free survival (LRFS), distant disease-free survival (DDFS), progression-free survival (PFS), and pathological complete response (pCR). This meta-analysis was registered in PROSPERO (CRD42023459282).

Results: The meta-analysis, including 129 studies with approximately 1,065,000 patients, re-ported that young breast cancer (YBC) patients had worse OS (HR = 1.30; 95% CI: 1.17 - 1.43; I² = 93%; P < 0.01), DFS (HR = 1.58; 95% CI: 1.47 - 1.70; I² = 68%; P < 0.01), BCSS (HR = 1.28; 95% CI: 1·09 - 1.49; I² = 95%; P < 0.01), LRFS (HR = 2.05; 95% CI: 1.59 - 2.59; I² = 70%; P < 0.01), DDFS (HR = 1.44; 95% CI: 1.11 - 1.87; I² = 91%; P < 0.01), and PFS (HR = 1.54; 95% CI: 1.16 - 2·03; I² = 90%; P < 0.01) and a greater pCR rates than non-young breast cancer (NYBC) patients (odds ratio (OR) = 1.45; 95% CI: 1.16 - 1.82; I² = 87%; P < 0.01). Subgroup analysis demonstrated that, compared with NYBC patients, certain differences were found in the prognoses of YBC patients with different molecular subtypes, regions, and stages.

Discussion: This meta-analysis confirmed that YBC patients have worse survival outcomes than NYBC patients, despite having higher pCR rates. Subgroup analyses demonstrated that outcomes varied by molecular subtype, region, and disease stage. These findings underscore the importance of early screening, enhanced patient education, and tailored treatment strategies for YBC patients.

Conclusion: Patients with YBC had worse OS, DFS, BCSS, LRFS, DDFS, PFS, and greater pCR rates than NYBC patients.

Objective: To analyze LUAD cases in The Cancer Genome Atlas (TCGA), the mRNA expression-based stemness index (mRNAsi) was used. Models of cancer immunity and LUAD prognosis were developed on the basis of correlations between immune and stem cell genes.

Methods: We investigated the differential expression of mRNA dryness index (mRNAsi) in LUAD, survival prognosis, and correlation with clinical parameters. Iden-tify key mRNAsi-related modules and genes by weighted gene co-expression network analysis (WGCNA). Gene set enrichment analysis (GSEA/GSVA) was used to identify stem cell markers and immune-related differentially expressed genes (SC IRGs), and 10 key genes were enriched. Subgroup enrichment, gene mutations, genetic correlated-ness, gene expression, immunity, tumor mutational burden (TMB), and drug sensitivity were further performed in the comprehensive analysis of pivot genes and subgroups.

Results: Compared with normal cells, LUAD cells presented significantly greater mRNAsi values through differential expression analysis. The mRNAsi was highly cor-related with clinical parameters (age, sex, and T stage). On the basis of WGCNA, blue-green and brown modules were identified as the most significant modules (including positive and negative correlations) associated with mRNAsi expression. The functions and pathways of the two mRNAsi-related modules were enriched mainly in tumor oc-currence, development, and metastasis. Cox regression analysis was used to identify 30 SCIRGs associated with prognosis by combining the stem cell indices of the DEGs and the immune-related DEGs. A LASSO regression model was constructed after 10 DEGs related to the prognosis of patients with LUAD were detected. There were significant differences between the high-risk and low-risk groups in terms of GSEA/GSVA, im-mune cell correlation, clinical correlation, etc., following model validation (P<0.05).

Discussion: There are a total of 10 genes in our study model, including four key pre-dictors: DGRIK2, PTTG1, LGR4, and PDGFB. The other 6 genes need to be further delineated and verified. To date, our research has some limitations and has not been validated in cell or animal experiments. These findings provide a relevant theoretical basis for subsequent experimental research on lung adenocarcinoma stem cells. Further research into these cancer stem cell genes will increase the likelihood that they play a role in cancer. There is an opportunity to use it as a therapeutic target for targeted ther-apy for lung adenocarcinoma in the future.

Conclusion: mRNAsi is associated with immunity, which was previously overlooked in the gene analysis of LUAD stem cells. These key genes have a strong overall corre-lation, which can be achieved by inhibiting the stemness characteristics of cancer cells, which may lay the foundation for future research on LUAD.

Introduction: Esophageal squamous cell carcinoma (ESCC) stands as one of the deadliest cancers globally. Given the urgent clinical need for more precise and comprehen-sive therapeutic strategies, the phytocompound methylophiopogonanone A (MO-A) demon-strates the potential as a candidate for ESCC treatment. This study aimed to verify the ther-apeutic effect of MO-A against ESCC and unveil its underlying mechanism.

Methods: Three compound-protein interaction databases were utilized to predict the molec-ular targets of MO-A. Subsequently, potential therapeutic targets of ESCC were identified based on the GEO database. KEGG pathway and GO function enrichment analyses were then performed by using these two sets of targets, respectively. Through the integrative anal-ysis of these two target sets, core targets of MO-A with therapeutic potential against ESCC were determined. Protein-protein interaction network analyses and molecular dockings were executed by using these targets. Two human-derived ESCC cell lines were enrolled for bio-logical validation, including cell viability, colony formation, and cell cycle assays.

Results: This study predicted 200 potential targets of MO-A and uncovered 138 key targets associated with the progression of ESCC. Enrichment analyses and PPI networks under-scored the involvement of cell cycle-related genes in ESCC development. Four proteins were determined as core MO-A targets for ESCC treatment, including AURKA, AURKB, CDC25B, and TOP2A, which partake in the regulation of the cell cycle. Finally, the inhibi-tory effect of MO-A on ESCC cell proliferation was validated in vitro, primarily through inducing cell cycle arrest at the G2/M phase in ESCC cells.

Discussion: These results revealed the anti-ESCC potential of MO-A, a plant-derived fla-vonoid, using integrated bioinformatics and biological experiments. While findings provide a mechanistic basis for the efficacy of MO-A, limitations include reliance on computational and in vitro models. Further studies should be conducted to evaluate the pharmacological properties and safety of MO-A across multiple models, alongside more comprehensive structure-activity relationship studies to inform drug optimization prior to clinical transla-tion.

Conclusion: MO-A can impede ESCC growth by triggering cell cycle G2/M arrest, posi-tioning it as a novel and promising phytocompound for ESCC therapy.

Background: CCAAT/Enhancer-Binding Protein Beta (CEBPB) is an important transcription factor that regulates tumor progression. However, the mechanism by which CE-BPB regulates the progression of Oral Squamous Cell Carcinoma (OSCC) remains incom-pletely understood. Tumor progression depends on complex intercellular interactions within the tumor microenvironment. The purpose of this study was to investigate the role and epige-netic regulatory mechanisms of CEBPB in interactions between OSCC cells and tumor-infil-trating immune cells.

Methods: Bulk RNA-seq, ChIP-seq, and scRNA-seq data were obtained from The Cancer Ge-nome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The HOMER algorithm was employed to identify enhancers and predict the CEBPB-binding mo-tif. Cell cluster analysis, functional enrichment, and intercellular interaction analysis were per-formed using the "Seurat" R package. H3K27ac enrichment at GAS6 enhancers was validated by ChIP-qPCR. Metastatic OSCC cells with CEBPB knockdown or GAS6 overexpression were established and co-cultured with THP-1 cells. IL-10 and IL-6 secretion from co-cultured THP-1 cells was detected via ELISA. Chemotaxis of OSCC cells toward THP-1 cells was assessed through a Transwell assay.

Results: CEBPB was upregulated in OSCC and correlated with poor prognosis. By integrating H3K27ac ChIP-seq and bulk RNA-seq data, 131 CEBPB-regulated enhancer-controlled genes were identified in lymph node metastatic OSCC cells. scRNA-seq analysis revealed eight ma-jor cell clusters in primary foci and lymph node metastases, including T/NK cells, malignant epithelial cells, B/plasma cells, macrophages, fibroblasts, dendritic cells, endothelial cells, and mast cells, with the malignant epithelial cells stratified into distinct sub-clusters. CEBPB ex-pression was elevated in malignant epithelial cells of lymph node metastases compared to pri-mary foci. Furthermore, 15 pairs of enhanced ligand-receptor interactions were identified in lymph node metastases relative to primary foci. GAS6 was a CEBPB-regulated enhancer-con-trolled gene, primarily mediating interactions between malignant cells and macrophages. CE-BPB knockdown in metastatic OSCC cells significantly impaired their chemotaxis toward co-cultured THP-1 cells, and downregulated IL-10/IL-6 secretion and CD206 expression in co-cultured THP-1 cells. Conversely, GAS6 overexpression reversed these inhibitory effects.

Conclusion: CEBPB activated GAS6 transcription in metastatic OSCC cells. The CE-BPB/GAS6 axis in metastatic OSCC cells enhanced their chemotaxis toward macrophages and promoted the M2 polarization of macrophages, thereby facilitating the establishment of an immunosuppressive microenvironment.

Phospholipids play a crucial role in various aspects of cancer biology, including tumor progression, metastasis, and cell survival. Recent studies have highlighted the signifi-cance of phospholipid metabolism and signaling in multiple cancer types, such as breast, cer-vical, prostate, bladder, colorectal, liver, lung, melanoma, mesothelioma, and oral cancer. Al-terations in phospholipid profiles, particularly in phosphatidylcholine and phosphatidylethan-olamine, have been identified as potential biomarkers for cancer diagnosis and prognosis. Moreover, specific phospholipids and their metabolic pathways have been implicated in cancer cell proliferation, migration, invasion, and resistance to therapy. Enzymes involved in phos-pholipid metabolism, such as phospholipases, choline kinase, and autotaxin, have emerged as promising therapeutic targets. The harmony between phospholipids and oncogenic signaling pathways, such as PI3K/AKT and Wnt/β-catenin, further emphasizes their importance in can-cer progression. Additionally, phospholipids have been shown to modify the tumor microen-vironment, influencing immune responses and angiogenesis. The application of advanced lip-idomic profiling techniques, such as mass spectrometry, has facilitated the identification of novel phospholipid biomarkers and provided insights into the metabolic reprogramming of cancer cells. Furthermore, phospholipid-based nanocarriers have demonstrated potential in tar-geted drug delivery and cancer immunotherapy. In conclusion, the multifaceted roles of phos-pholipids in cancer biology highlight their significance as diagnostic markers, prognostic in-dicators, as well as therapeutic targets, offering new avenues for cancer management and treat-ment. This review is conducted in order to answer three questions: What is the role of phos-pholipids in different types of cancer? What are the key lipidomic biomarkers for different cancers? What are the key effects of phospholipids on various types of cancer cell survival?

Introduction: The incidence of brain metastases in patients diagnosed with ad-vanced lung cancer is high, drawing significant attention to the risk factors associated with this progression.

Methods: A total of 252 advanced non-small cell lung cancer (NSCLC) patients with brain metastases were enrolled in this study between July 2018 and December 2023 from our hos-pital. Additionally, driver genes, including EGFR, ALK, ROS1, KRAS, and RET, were doc-umented. Next-generation targeted sequencing of a 168-gene panel was conducted on all col-lected samples to explore the association between tumor genomic complexity and risk factors for NSCLC with brain metastases.

Results: Among 252 lung cancer patients with brain metastases enrolled in this research, the most prevalent driver gene was EGFR, accounting for 39.29% (99 patients). Other driver gene mutations, such as KRAS, ALK, ROS1, and RET, accounted for 3.57%, 7.14%, 2.78%, and 0.4%, respectively. Kaplan-Meier analysis showed that patients with EGFR mutations had a more favorable overall survival (OS) compared to those without the mutation (P < 0.0001). Additionally, patients with ALK fusions had longer survival times compared to those with wild-type genes (P = 0.0021). In this study, patients were divided into two groups based on the presence or absence of copy-number alterations. Further survival analysis revealed that patients with copy-number alterations experienced significantly shorter overall survival com-pared to the control group (P = 0.041).

Discussion: This study underscores the crucial role of driver mutations and genomic instability in advanced NSCLC with brain metastases, where EGFR and ALK alterations are linked to better survival. In contrast, high genomic complexity is associated with worse outcomes.

Conclusion: Driver gene mutations are present in more than half of the patients with central nervous system (CNS) failure. Genomic instability, characterized by the number of co-occur-ring mutated genes and copy-number alterations, is a risk factor associated with shorter sur-vival time.

Introduction: Ovarian clear cell carcinoma (OCCC) accounts for about 5% of all epithelial ovarian cancers. Currently, its treatment mainly refers to high-grade serous carci-noma (HGSC). This study aimed to explore differences in clinical characteristics between OCCC and HGSC and studied the reasons for the differences.

Methods: The data of OCCC and HGSC cases were obtained from the SEER database. Uni-variate and multivariate Cox regression analyses were used to explore the prognostic factors. Next, whole exome sequencing (WES) was performed on 15 clinically selected OCCC cases and 16 HGSC cases to identify significantly mutated genes (SMGs). Further analysis included calculating tumor mutation burden (TMB) and predicting potential target drugs based on the identified mutations.

Results: 3493 OCCC and 10266 HGSC patients from the SEER database were included in the study. Survival analysis showed that the overall survival (OS) of stage I-II OCCC was better than that of stage I-II HGSC, while the OS of stage III-IV OCCC was worse than that of stage III-IV HGSC. Further subgroup analysis showed that for the OCCC group, age ≥ 60 years, bilateral tumor distribution, tumor size ≥ 87mm, and stage III-IV were independent risk factors for OS. For HGSC patients, tumor size ≥ 87mm was an independent protective factor for OS. WES results suggested that among the top 20 SMGs of OCCC in stage III-IV patients, DNAH2, LAMA5, MUC19, NOTCH1, PCLO, SYNE2, TACC2, and ZNF469 were 8 specific SMGs that distinguish III-IV OCCC from III-IV HGSC. In addition, the stage I-II OCCC group had the highest TMB, and the lowest was the stage III-IV OCCC.

Discussion: Our findings challenge the conventional uniform therapeutic approach for ovarian carcinomas by revealing stage-dependent SMGs between OCCC and HGSC. However, limi-tations such as the retrospective SEER analysis, small WES cohort, and population-specific driver gene variations require cautious interpretation of the findings.

Conclusions: The independent prognostic factors identified in this study provide a theoretical basis for individualized prognosis judgment in OCCC and HGSC. The SMGs and TMB levels may serve as valuable indicators for prognosis and evaluating targeted therapy or immunother-apy efficacy. Druggable genes such as NOTCH1 and RYR3 offer promising therapeutic tar-gets, while stage-specific pathway enrichments reveal potential intervention strategies. Further validation in larger cohorts is needed to confirm these findings. Our study advances the under-standing of molecular heterogeneity in ovarian cancer and lays the groundwork for personal-ized treatment strategies, ultimately improving patient outcomes.

Introduction: Sex-determining region Y-box 9 (SOX9) is a transcription factor frequently overexpressed in breast cancer, playing a critical role in tumor initiation, progression, and therapeutic resistance. While its oncogenic potential is recognized, the underlying molecular mechanisms remain incompletely elucidated. This study aimed to investigate the functional role of SOX9 in breast cancer, specifically focusing on its interaction with the EGFR/STAT3 signaling pathway.

Methods: The study integrated bioinformatics analyses with functional assays in breast cancer cell lines to determine the effects of SOX9 modulation on cell proliferation, migration, and invasion, and to elucidate its connection with the EGFR/STAT3 signaling axis.

Results: Our findings demonstrate that SOX9 promotes breast cancer cell proliferation, migration, and invasion. Mechanistically, this occurs through the activation of the EGFR/STAT3 signaling axis. Furthermore, targeting SOX9 effectively attenuated these oncogenic phenotypes in vitro.

Discussion: The elucidation of SOX9's role in activating the EGFR/STAT3 pathway significantly advances our understanding of its oncogenic mechanisms in breast cancer. These findings are consistent with existing literature on SOX9's pro-tumorigenic impact and the established role of EGFR/STAT3 signaling in cancer progression, highlighting a crucial regulatory link. This newly identified SOX9-EGFR/STAT3 axis not only reinforces SOX9's prognostic value but also strongly supports its exploration as a novel therapeutic target.

Conclusion: These findings identify SOX9 as a key regulator of the EGFR/STAT3 signaling pathway in breast cancer. This highlights the potential of SOX9 as both a prognostic biomarker and a promising target for drug therapy in breast cancer.